IIT Kharagpur Team Develops System To Predict COVID-19 Spread To Help Decision-Making
Although the implementation fails to generate stable and reliable predictions at the moment, the trend clearly reveals that the disease is going to stay in the country for many more months, says the IIT Kharagpur team.
The Indian Institute of Technology Kharagpur, or IIT Kharagpur, has developed a system to predict the spread of coronavirus cases to enable decision-making in the health-care industry, on the economy and academics. The data used for predicting the spread of COVID-19 covers the entire country and most affected states including Maharashtra, Tami Nadu, Delhi, Gujarat, Uttar Pradesh, Rajasthan, West Bengal and Madhya Pradesh.
As per the IIT Kharagpur study, the implementation, although, “fails to generate stable and reliable predictions at the moment, the trend clearly reveals that the disease is going to stay in the country for many more months”.
Prof Abhijit Das of the Department of Computer Science and Engineering, IIT Kharagpur, has developed this “logistic model which can be used to fit the available daily counts” of infection cases.
“The [information] uses only the daily infection counts available in the public domain without accessing sensitive information pertaining to medical records or contact-tracing data for a large fraction of the population. Despite that, the prediction curves show remarkably good fitting with the past data, and can be used for future planning”, Prof Das said in a statement issued by the institute.
“Our study indicates that India is yet to achieve a steady pattern in the spread of the disease. It is unlikely to get rid of COVID-19 before the end of September 2020,” added Prof Das. “This does not leave us in a region of comfort, but the reality has to be accepted, and appropriate plans must be chalked out to address all the issues associated with the outbreak of the pandemic.”
Director of IIT Kharagpur, Prof Virendra Kumar Tewari in a statement said, “People have been living in an uncertain black box without the knowledge about which way life is going to turn and how to plan their activities. A study like this based on a clear statistical model will enable them to understand and plan their way forward.” Prof Tiwari further added: “The model though experimental could prove to be helpful in planning our academic semester and policy matters related to the institute and the campus under the current circumstances.”
Factors Affecting the Study
The predictions for the future, however, changes quite rapidly with time, said the statement. Several potential factors affect the system of prediction. Different mobility patterns of Indian people in different phases of lockdown, large-scale migration of laborers, change in diagnostic facilities and evolution of the coronavirus account for the changes in the pattern of predicting the rise or fall of positive cases.
The study added that these factors are “well beyond the control of the logistic model or any other currently known prediction model” for that matter.